In our framework, context and commonsense modeling is performed using GRU cells [1]}. GRU cells take as input \(y_t\)  and update its hidden state from \(h_{t-1}\)  to \(h_t\)  using the transformation: \(h_t = GRU(h_{t-1}, y_t)\) . New hidden state \(h_t\)  also serves as the output of the current step. The cell is parameterized by weights \(W\)  and biases \(b\)  of appropriate sizes depending upon the
input \(y_t\)  and output \(h_t\) .
We use five Bidirectional GRU cells \(GRU_C, GRU_Q, GRU_R, GRU_I\) , and \(GRU_E\)  for modeling context state, internal state, external state, intent state, and emotion state respectively. For ease of representation we formulate the different states with unidirectional GRU cells here.
